scmvae 1.0.0

a comprehensive single-cell multimodal analysis python package based on mixed variational autoencoder

The paired measurement of multiple modalities, known as multimodal analysis, is an exciting frontier for connecting single-cell genomics with epitopes and functions. Mapping of transcriptomes in single-cells and the integration with cell phenotypes enable a better understanding of cellular states. However, assembling these paired omics into a unified representation of the cellular state remains challenging with the unique technical characteristics of each measurement. In this work, we present a python package for single-cell multimodal analysis based on a mixing variational autoencoder that not only joins single-cell transcriptomes and epitopes but also enables simultaneous execution of independent modal analysis.